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Customer analytics

Customer Behaviour Analytics

Compare shopping behavior and customer segments by product category, age group and subscription status.

PythonPandasMySQLSQLExcelPower BIDAX
3.9K customers01 / scope
$59.76 average purchase02 / scope
3.75 average review rating03 / scope
73% non-subscribers04 / scope
01

Business question

How do purchase patterns and customer characteristics vary across categories, age brackets and subscription status?

02

Data

Customer shopping records covering product categories, age brackets, subscription status, purchase amounts and review ratings.

03

Approach

  1. 01Clean and prepare records
  2. 02Compare segments in SQL and exploratory analysis
  3. 03Build an interactive Power BI dashboard
  4. 04Review category, age and subscription patterns
04

Analysis

Compared revenue and purchase volume across Clothing, Accessories, Footwear and Outerwear, and examined results across age brackets and subscription status.

What I builtInteractive customer behavior dashboard with KPI, category, age and subscription views.

05

Key findings

  • 01

    Non-subscribers made up 73% of customers; subscribers made up 27%.

  • 02

    Average purchase amount was $59.76; average review rating was 3.75.

  • 03

    The dashboard compared category performance and customer patterns across four age brackets.

06

Business context

The segment views provide a baseline for comparing customer spend and purchase volume across product and subscription groups.

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